The field of Astrostatistics has been growing rapidly over the past decade,  with advanced statistical methods entering the standard techniques broadly used by astronomers.  Several astrostatistics associations have been established over this period with the primary  goal of fostering interdisciplinary collaborations. Such collaborations have resulted in advancing both the analysis of astronomical data as well as statistical methodology.  Astronomical data pose unique challenges to statisticians: analysis requires understanding the systematics in the data collection process, contaminating factors, and the behavior of instruments, an ability to handle signals with large dynamic range and complex hierarchical models, and a recognition that data acquisition is often not a repeatable or reproducible process.These challenges resulted in developments of new statistical methods, e.g., improvements in MCMC sampling strategies in reaction to complex astrophysical parameter spaces, establishing the magnitudes of corrections to instrument calibration even in the absence of an absolute reference, developing multi-stage strategies to account for systematic uncertainties present in atomic data and instrument calibration, computing change points in 4-dimensional data cubes, spatial segmentations in unbinned data, disambiguating photons from overlapping sources, etc.The goals of the proposed session are to highlight new results originating from ongoing collaborative research, increase awareness of astronomical data problems among statisticians, and foster collaborations between astronomers and statisticians. The invited speakers are from diverse geographical locations and include statisticians and astronomers who have been involved in active astrostatistics collaborations. They will provide their perspective on astrostatistics research and present case studies of several astronomical data problems and how they developed working solutions.

The confirmed speakers and the topics of presentations:

Jogesh Babu is a statistician who has been working with astronomers for more than three decades and witnessed formations of the astrostatistics associations.  He along with his astronomer colleague Eric Feigelson coined the term “Astrostatistics” when they published a book by the same title in 1996. He will present a historical perspective on a rapid growth of astrostatistics.  

Yang Chen is a statistician representing the ASA Astrostatistics Interest Group. She will present statistical issues in instrument calibration and discuss ML methods to determine solar flare propensity.

David Van Dyk is a statistician and a founding member of CHASC astrostatistics collaboration and will highlight CHASC activities.

Gwendolyn Eadie is an astrostatistician and will discuss the status of astrostatistics in Canada. She will also highlight recent work in her interdisciplinary research group including Bayesian inference for analysis of star clusters and understanding bias resulting from data collection, functional principal component analysis for studying stellar chemical composition, and spatial point process models for discovering new galaxies.

Thomas Loredo is an astrostatistician and has been a co-chair of the Rubin Observatory LSST Informatics and Statistics Science Collaboration. He will highlight results of the competition challenges organized by the LSST ISSC such as time-series classification, time-delay, and tomography challenges.

This proposal comes from the Council of the International Astrostatistics Association (IAA; http://iaa.mi.oa-brera.inaf.it/IAA/home.html) and is supported by ISI Astrostatistics Special Interest Group (https://www.isi-web.org/isi-community/committees/astrostatistics), which has representatives from sister organizations: IAU, IEEE, ASA, and AAS.

Organiser: Aneta Siemiginowska 

Chair: Aneta Siemiginowaska 

Speaker: Jogesh Babu 

Speaker: Gwendolyn Eadie 

Speaker: David Stenning 

Speaker: Yang Chen 

Speaker:  Thomas Loredo